De-novo SuperTranscriptome assembly from the nodal root growth zone of maize inbred line FR697

Certain cultivars of maize show increased resistance to water deficit conditions by maintenance of root growth. To better understand the molecular mechanisms related to this adaption, nodal root growth zone samples were collected from the reference inbred line B73 and inbred line FR697, which exhibits a relatively greater ability to maintain root elongation under water

Design and Evaluation of a Longitudinal Method to Measure Physician Burnout in the Clinical Workflow

Burnout, a condition characterized by emotional exhaustion, listlessness, and an inability to cope, is demonstrably more prevalent among healthcare providers than other occupations. Burnout is fundamentally a longitudinal problem, but traditional instruments for measurement such as the Maslach Burnout Inventory (MBI) and the Professional Fulfillment Index (PFI) are time-consuming, expensive, and complex to administer, making

Analysis and Dissemination of School-based Immunization Data to Improve Public Health Outcomes in Missouri

In Missouri, immunization is required for both public and private school students against common vaccine-preventable diseases (VPDs) including polio, pertussis, varicella, measles, mumps, and rubella; however, parents may forego vaccination for their child by claiming medical or religious exemptions. Like many states across the US, Missouri is experiencing increasing vaccine exemption rates. However, health officials

Regulation of gene expression by DNA methylation with cytotoxic T lymphocytes evaluation in consensus molecular subtypes of colorectal cancer

Background: Low cytotoxic T lymphocyte (CTLs) infiltration in colorectal cancer (CRC) tumors is a challenge to treatment with immune checkpoint inhibitors. Consensus molecular subtypes (CMS) classify patients based on tumor attributes, and CMS1 patients include the majority of patients with high CTL infiltration and “inflamed” tumors. Epigenetic modification plays a critical role in gene expression

Leveraging Unsupervised Machine Learning To Find Trends In The Textual Warnings Generated Using Multi-Modality Time Series Sensor Data

With technology and the internet of things (IoT), smart health care is no longer a dream. The devices that wouldn’t usually be generally expected to have an internet connection can communicate with the network independent of human action, and this is referred to as the internet of things. These devices, in our case, are the

Information Extraction Framework for Facilitating the Assessment of the Quality of Radiology Interpretations

Assessing the quality of imaging interpretations requires that the results of radiological interpretations be compared with those of subsequent surgical-pathology results, when available. The manual process is inherently slow, tedious and expensive, and unless systematic errors occur in the interpretations, discrepancies are unlikely to be detected. Classical computational methods using Natural Language Processing entail using

Abnormal liver function and adverse health outcomes in COVID-19: A multicenter, retrospective analysis of 14,872 patients from the Cerner Real-World DataTM de-identified COVID-19 cohort

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been associated with liver impairment and abnormalities in liver function tests. However, associations between hepatic impairment and patient health outcomes have not been well-studied in large cohorts. In this US-based, multicenter retrospective cohort study, we analyze the impact of abnormalities in liver function

Methods for Measuring Geodiversity in Large Overhead Imagery Datasets

This research introduces some of the first geo-computational methods to address a key gap in the artificial intelligence (AI) and big data literature as it relates to the geosciences and remote sensing: the lack of understanding of the global feature representativeness of labels in large remotely-sensed imagery (RSI) datasets. Issues of data fairness, heterogeneity and

The Genescape Allele Catalog Development for Precise Identification of Causative SNPs

Next-generation sequencing (NGS) has become more popular in the modern-day. Large amounts of next-generation resequencing data have been generated and are available online for various organisms including soybeans. However, current genome-wide association study (GWAS) prediction tools simply identify the most significant SNP based on Manhattan plots and still have some limitations in pinpointing the exact

Evaluating the effectiveness of transfer-learning with DeepVariant

Genomic data has become ubiquitous for bioinformaticians; however, successfully inferring biological meaning depends upon the sensitive prediction of differences between genomes. The most popular method to infer short sequence variants is the Genome Analysis Toolkit (GATK). While GATK provides rigorous guidelines, the methods require knowledge-intensive refinement as software and sequencing technologies advance. A recent advancement

News